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Meteorological conditions are heterogeneous factors for COVID-19 risk in China

Whether meteorological factors influence COVID-19 transmission is an issue of major public health concern, but available evidence remains unclear and limited for several reasons, including the use of report date which can lag date of symptom onset by a considerable period. We aimed to generate relia...

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Autores principales: Xiao, Shuang, Qi, Hongchao, Ward, Michael P., Wang, Wenge, Zhang, Jun, Chen, Yue, Bergquist, Robert, Tu, Wei, Shi, Runye, Hong, Jie, Su, Qing, Zhao, Zheng, Ba, Jianbo, Qin, Ying, Zhang, Zhijie
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Elsevier Inc. 2021
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8050398/
https://www.ncbi.nlm.nih.gov/pubmed/33872647
http://dx.doi.org/10.1016/j.envres.2021.111182
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author Xiao, Shuang
Qi, Hongchao
Ward, Michael P.
Wang, Wenge
Zhang, Jun
Chen, Yue
Bergquist, Robert
Tu, Wei
Shi, Runye
Hong, Jie
Su, Qing
Zhao, Zheng
Ba, Jianbo
Qin, Ying
Zhang, Zhijie
author_facet Xiao, Shuang
Qi, Hongchao
Ward, Michael P.
Wang, Wenge
Zhang, Jun
Chen, Yue
Bergquist, Robert
Tu, Wei
Shi, Runye
Hong, Jie
Su, Qing
Zhao, Zheng
Ba, Jianbo
Qin, Ying
Zhang, Zhijie
author_sort Xiao, Shuang
collection PubMed
description Whether meteorological factors influence COVID-19 transmission is an issue of major public health concern, but available evidence remains unclear and limited for several reasons, including the use of report date which can lag date of symptom onset by a considerable period. We aimed to generate reliable and robust evidence of this relationship based on date of onset of symptoms. We evaluated important meteorological factors associated with daily COVID-19 counts and effective reproduction number (R(t)) in China using a two-stage approach with overdispersed generalized additive models and random-effects meta-analysis. Spatial heterogeneity and stratified analyses by sex and age groups were quantified and potential effect modification was analyzed. Nationwide, there was no evidence that temperature and relative humidity affected COVID-19 incidence and R(t). However, there were heterogeneous impacts on COVID-19 risk across different regions. Importantly, there was a negative association between relative humidity and COVID-19 incidence in Central China: a 1% increase in relative humidity was associated with a 3.92% (95% CI, 1.98%–5.82%) decrease in daily counts. Older population appeared to be more sensitive to meteorological conditions, but there was no obvious difference between sexes. Linear relationships were found between meteorological variables and COVID-19 incidence. Sensitivity analysis confirmed the robustness of the association and the results based on report date were biased. Meteorological factors play heterogenous roles on COVID-19 transmission, increasing the possibility of seasonality and suggesting the epidemic is far from over. Considering potential climatic associations, we should maintain, not ease, current control measures and surveillance.
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spelling pubmed-80503982021-04-16 Meteorological conditions are heterogeneous factors for COVID-19 risk in China Xiao, Shuang Qi, Hongchao Ward, Michael P. Wang, Wenge Zhang, Jun Chen, Yue Bergquist, Robert Tu, Wei Shi, Runye Hong, Jie Su, Qing Zhao, Zheng Ba, Jianbo Qin, Ying Zhang, Zhijie Environ Res Article Whether meteorological factors influence COVID-19 transmission is an issue of major public health concern, but available evidence remains unclear and limited for several reasons, including the use of report date which can lag date of symptom onset by a considerable period. We aimed to generate reliable and robust evidence of this relationship based on date of onset of symptoms. We evaluated important meteorological factors associated with daily COVID-19 counts and effective reproduction number (R(t)) in China using a two-stage approach with overdispersed generalized additive models and random-effects meta-analysis. Spatial heterogeneity and stratified analyses by sex and age groups were quantified and potential effect modification was analyzed. Nationwide, there was no evidence that temperature and relative humidity affected COVID-19 incidence and R(t). However, there were heterogeneous impacts on COVID-19 risk across different regions. Importantly, there was a negative association between relative humidity and COVID-19 incidence in Central China: a 1% increase in relative humidity was associated with a 3.92% (95% CI, 1.98%–5.82%) decrease in daily counts. Older population appeared to be more sensitive to meteorological conditions, but there was no obvious difference between sexes. Linear relationships were found between meteorological variables and COVID-19 incidence. Sensitivity analysis confirmed the robustness of the association and the results based on report date were biased. Meteorological factors play heterogenous roles on COVID-19 transmission, increasing the possibility of seasonality and suggesting the epidemic is far from over. Considering potential climatic associations, we should maintain, not ease, current control measures and surveillance. Elsevier Inc. 2021-07 2021-04-16 /pmc/articles/PMC8050398/ /pubmed/33872647 http://dx.doi.org/10.1016/j.envres.2021.111182 Text en © 2021 Elsevier Inc. All rights reserved. Since January 2020 Elsevier has created a COVID-19 resource centre with free information in English and Mandarin on the novel coronavirus COVID-19. The COVID-19 resource centre is hosted on Elsevier Connect, the company's public news and information website. Elsevier hereby grants permission to make all its COVID-19-related research that is available on the COVID-19 resource centre - including this research content - immediately available in PubMed Central and other publicly funded repositories, such as the WHO COVID database with rights for unrestricted research re-use and analyses in any form or by any means with acknowledgement of the original source. These permissions are granted for free by Elsevier for as long as the COVID-19 resource centre remains active.
spellingShingle Article
Xiao, Shuang
Qi, Hongchao
Ward, Michael P.
Wang, Wenge
Zhang, Jun
Chen, Yue
Bergquist, Robert
Tu, Wei
Shi, Runye
Hong, Jie
Su, Qing
Zhao, Zheng
Ba, Jianbo
Qin, Ying
Zhang, Zhijie
Meteorological conditions are heterogeneous factors for COVID-19 risk in China
title Meteorological conditions are heterogeneous factors for COVID-19 risk in China
title_full Meteorological conditions are heterogeneous factors for COVID-19 risk in China
title_fullStr Meteorological conditions are heterogeneous factors for COVID-19 risk in China
title_full_unstemmed Meteorological conditions are heterogeneous factors for COVID-19 risk in China
title_short Meteorological conditions are heterogeneous factors for COVID-19 risk in China
title_sort meteorological conditions are heterogeneous factors for covid-19 risk in china
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8050398/
https://www.ncbi.nlm.nih.gov/pubmed/33872647
http://dx.doi.org/10.1016/j.envres.2021.111182
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